import json
import os
import unittest
from typing import Tuple

from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from transformers.testing_utils import require_phonemizer

from ...test_tokenization_common import TokenizerTesterMixin



@require_phonemizer
class   lowercase_       (	a_		,					unittest.TestCase						):
							_lowerCamelCase		=						WavaVecaPhonemeCTCTokenizer
							_lowerCamelCase		=						False



							def 			UpperCamelCase			(		self							):
													super().setUp()

													_snake_case		:	int							=       (
													    "<s> <pad> </s> <unk> n s t ə l a i k d m ɛ ɾ e ɪ p o ɐ z ð f j v b ɹ ʁ ʊ iː r w ʌ u ɡ æ aɪ ʃ h ɔ ɑː "
													    "ŋ ɚ eɪ β uː y ɑ̃ oʊ ᵻ eː θ aʊ ts oː ɔ̃ ɣ ɜ ɑ dʒ əl x ɜː ç ʒ tʃ ɔː ɑːɹ ɛ̃ ʎ ɔːɹ ʋ aː ɕ œ ø oːɹ ɲ yː "
													    "ʔ iə i5 s. tɕ ?? nʲ ɛː œ̃ ɭ ɔø ʑ tʲ ɨ ɛɹ ts. rʲ ɪɹ ɭʲ i.5 ɔɪ q sʲ u5 ʊɹ iɜ a5 iɛ5 øː ʕ ja əɜ th ɑ5 "
													    "oɪ dʲ ə5 tɕh ts.h mʲ ɯ dʑ vʲ e̞ tʃʲ ei5 o5 onɡ5 ɑu5 iɑ5 ai5 aɪɚ kh ə1 ʐ i2 ʉ ħ t[ aɪə ʲ ju ə2 u2 oɜ "
													    "pː iɛɜ ou5 y5 uɜ tː uo5 d[ uoɜ tsh ɑɜ ɵ i̪5 uei5 ɟ aɜ ɑɨ i.ɜ eʊ o2 ɐ̃ ä pʲ kʲ n̩ ɒ ph ɑu2 uɨ əɪ ɫ ɬ "
													    "yɜ bʲ ɑ2 s̪ aiɜ χ ɐ̃ʊ̃ 1 ə4 yæɜ a2 ɨː t̪ iouɜ ũ onɡɜ aɨ iɛ2 ɔɨ ɑuɜ o̞ ei2 iou2 c kː y2 ɖ oe dˤ yɛɜ "
													    "əʊ S ɡʲ onɡ2 u\" eiɜ ʈ ɯᵝ iou5 dZ r̝̊ i.2 tS s^ ʝ yə5 iɑɜ uə5 pf ɨu iɑ2 ou2 ər2 fʲ ai2 r̝ uəɜ ɳ əɨ "
													    "ua5 uɪ ɽ bː yu5 uo2 yɛ5 l̩ ɻ ərɜ ʂ i̪2 ouɜ uaɜ a. a.ː yæ5 dː r̩ ee ɪu ər5 i̪ ɜ æi u: i.ː t^ o1 ɪ^ "
													    "ai ueiɜ æː ɛɪ eə i. ɴ ie ua2 ɑ1 o4 tʃː o: ɑ: u1 N i̪1 au yæ2 u. qː yəɜ y: kʰ tʃʰ iʊ sx õ uo tʰ "
													    "uai5 bʰ u.ː uə2 ʊə d^ s̪ː yiɜ dʰ r. oe: i1 ɟː yu2 nʲʲ i̪4 uei2 tsʲ ɸ ĩ ɑ4 t̪ː eɑ u4 e: tsː ʈʰ ɡʰ "
													    "ɯɯ dʒʲ ʂʲ X ɵː uaiɜ tɕʲ ã t^ː ẽː yɛ2 cː i.1 ɛʊ dˤdˤ dʒː i4 ɡː yi ɕʲ ɟʰ pʰ dʑʲ yuɜ ua1 ua4 æiː ɐɐ "
													    "ui iou1 ʊː a1 iou4 cʰ iɛ1 yə2 ɖʰ ẽ ʒʲ ää ər4 iːː ɪː iɑ1 ər1 œː øi ɪuː cʰcʰ əː1 iː1 ũ kʰː o̞o̞ xʲ "
													    "ou1 iɛ4 e̞e̞ y1 dzː dʲʲ dʰː ɯᵝɯᵝ lː uo1 i.4 i: yɛ5ʲ a4"
													).split(" "							)
													_snake_case		:	int							=       dict(zip(UpperCamelCase_ ,							range(len(UpperCamelCase_							)							)							)							)

													_snake_case		:	Dict							=       {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

													_snake_case		:	Union[str, Any]							=       os.path.join(self.tmpdirname ,							VOCAB_FILES_NAMES["vocab_file"]							)
													with open(self.vocab_file ,							"w" ,							encoding="utf-8"							) as fp:
																			fp.write(json.dumps(UpperCamelCase_							) + "\n"							)



							def 			UpperCamelCase			(		self ,							lowercase_ ,							lowercase_=False ,							lowercase_=20 ,							lowercase_=5							):
													_snake_case		:	Optional[Any]							=       [(i, tokenizer.decode([i] ,							clean_up_tokenization_spaces=UpperCamelCase_							)) for i in range(len(UpperCamelCase_							)							)]
													_snake_case		:	List[Any]							=       list(filter(lambda lowercase_							: [t[0]] == tokenizer.encode(t[1] ,							do_phonemize=UpperCamelCase_							) ,							UpperCamelCase_							)							)
													if max_length is not None and len(UpperCamelCase_							) > max_length:
																			_snake_case		:	List[Any]							=       toks[:max_length]
													if min_length is not None and len(UpperCamelCase_							) < min_length and len(UpperCamelCase_							) > 0:
																			while len(UpperCamelCase_							) < min_length:
																									_snake_case		:	List[str]							=       toks + toks
        # toks_str = [t[1] for t in toks]
													_snake_case		:	Union[str, Any]							=       [t[0] for t in toks]

													# Ensure consistency
													_snake_case		:	int							=       tokenizer.decode(UpperCamelCase_ ,							clean_up_tokenization_spaces=UpperCamelCase_							)
													if " " not in output_txt and len(UpperCamelCase_							) > 1:
																			_snake_case		:	Optional[Any]							=       (
																			    tokenizer.decode([toks_ids[0]] ,							clean_up_tokenization_spaces=UpperCamelCase_							)
																			    + " "
																			    + tokenizer.decode(toks_ids[1:] ,							clean_up_tokenization_spaces=UpperCamelCase_							)
																			)
													if with_prefix_space:
																			_snake_case		:	List[str]							=       " " + output_txt
													_snake_case		:	Any							=       tokenizer.encode(UpperCamelCase_ ,							add_special_tokens=UpperCamelCase_							)
													return output_txt, output_ids



							def 			UpperCamelCase			(		self ,							**lowercase_							):
													kwargs.update(self.special_tokens_map							)
													return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname ,							**UpperCamelCase_							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Tuple							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)

													# check adding a single token
													tokenizer.add_tokens("xxx"							)
													_snake_case		:	Optional[int]							=       tokenizer("m xxx ɪ" ,							do_phonemize=UpperCamelCase_							).input_ids
													self.assertEqual(UpperCamelCase_ ,							[13, 392, 17]							)  # xxx should be last token

													tokenizer.add_tokens(["aaa", "bbb", "ccc"]							)
													_snake_case		:	Tuple							=       tokenizer("m aaa ɪ ccc" ,							do_phonemize=UpperCamelCase_							).input_ids
													self.assertEqual(UpperCamelCase_ ,							[13, 393, 17, 395]							)  # aaa and ccc should be after xxx and 2 after aaa

													_snake_case		:	Dict							=       tokenizer("maɪ c" ,							do_phonemize=UpperCamelCase_							).input_ids
													self.assertEqual(UpperCamelCase_ ,							[3, 200]							)  # mai should be <unk> (=3)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	List[str]							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)

													_snake_case		:	List[Any]							=       "Hello how are you"
													_snake_case		:	List[Any]							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)
													self.assertEqual(UpperCamelCase_ ,							"h ə l oʊ h aʊ ɑːɹ j uː"							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	List[str]							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)

													_snake_case		:	Optional[Any]							=       "Hello how are you"
													_snake_case		:	Tuple							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)
													self.assertEqual(tokenizer(UpperCamelCase_							).input_ids ,							tokenizer(UpperCamelCase_ ,							do_phonemize=UpperCamelCase_							).input_ids							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	int							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)
													_snake_case		:	Tuple							=       "Hello how are you"
													_snake_case		:	Optional[Any]							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)

													_snake_case		:	List[str]							=       tokenizer.decode(tokenizer(UpperCamelCase_							).input_ids							)

													self.assertEqual(UpperCamelCase_ ,							UpperCamelCase_							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Dict							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)

													_snake_case		:	Optional[int]							=       [
													    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
													    [24, 22, 5, 24, 22, 5, 77],
													]
													_snake_case		:	Tuple							=       tokenizer.decode(sample_ids[0]							)
													_snake_case		:	Tuple							=       tokenizer.batch_decode(UpperCamelCase_							)
													self.assertEqual(UpperCamelCase_ ,							batch_tokens[0]							)
													self.assertEqual(UpperCamelCase_ ,							["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"]							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	str							=       self.tokenizer_class.from_pretrained(
													    "facebook/wav2vec2-lv-60-espeak-cv-ft" ,							word_delimiter_token="|"							)
													tokenizer.add_tokens("|"							)

													_snake_case		:	int							=       "Hello how are you"
													_snake_case		:	Union[str, Any]							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)
													self.assertEqual(UpperCamelCase_ ,							"h ə l oʊ | h aʊ | ɑːɹ | j uː |"							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	List[Any]							=       self.tokenizer_class.from_pretrained(
													    "facebook/wav2vec2-lv-60-espeak-cv-ft" ,							word_delimiter_token="|"							)
													tokenizer.add_tokens("|"							)

													_snake_case		:	Any							=       "Hello how are you"
													_snake_case		:	str							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)
													self.assertEqual(tokenizer(UpperCamelCase_							).input_ids ,							tokenizer(UpperCamelCase_ ,							do_phonemize=UpperCamelCase_							).input_ids							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Optional[int]							=       self.tokenizer_class.from_pretrained(
													    "facebook/wav2vec2-lv-60-espeak-cv-ft" ,							word_delimiter_token="|"							)
													tokenizer.add_tokens("|"							)

													# fmt: off
													_snake_case		:	Union[str, Any]							=       [
													    [11, 5, 15, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 15, 8, tokenizer.word_delimiter_token_id, 98],
													    [tokenizer.word_delimiter_token_id, 24, 22, tokenizer.word_delimiter_token_id, 5, 24, 22, 5, 77],
													]
													# fmt: on

													# decode with word_del_token filter
													_snake_case		:	Union[str, Any]							=       tokenizer.decode(sample_ids[0]							)
													_snake_case		:	List[Any]							=       tokenizer.batch_decode(UpperCamelCase_							)
													self.assertEqual(UpperCamelCase_ ,							batch_tokens[0]							)
													self.assertEqual(UpperCamelCase_ ,							["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"]							)

													# decode with no word_del_token filter
													_snake_case		:	Optional[Any]							=       tokenizer.decode(sample_ids[0] ,							filter_word_delimiter_token=UpperCamelCase_							)
													_snake_case		:	List[Any]							=       tokenizer.batch_decode(UpperCamelCase_ ,							filter_word_delimiter_token=UpperCamelCase_							)
													self.assertEqual(UpperCamelCase_ ,							batch_tokens[0]							)
													self.assertEqual(UpperCamelCase_ ,							["k s ɾ | ɾ l | ɭʲ", "| j ð | s j ð s oːɹ"]							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Any							=       self.tokenizer_class.from_pretrained(
													    "facebook/wav2vec2-lv-60-espeak-cv-ft" ,							word_delimiter_token="|"							)
													tokenizer.add_tokens("|"							)

													_snake_case		:	Optional[Any]							=       "Hello how are you"
													_snake_case		:	Tuple							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)

													_snake_case		:	Any							=       tokenizer.decode(tokenizer(UpperCamelCase_							).input_ids ,							filter_word_delimiter_token=UpperCamelCase_							)

													self.assertEqual(UpperCamelCase_ ,							UpperCamelCase_							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Any							=       self.tokenizer_class.from_pretrained(
													    "facebook/wav2vec2-lv-60-espeak-cv-ft" ,							word_delimiter_token="|"							)
													tokenizer.add_tokens("|"							)

													_snake_case		:	Optional[int]							=       "Hello how are you"
													_snake_case		:	List[Any]							=       tokenizer.phonemize(UpperCamelCase_ ,							phonemizer_lang="en-us"							)

													_snake_case		:	Union[str, Any]							=       tokenizer.decode(tokenizer(UpperCamelCase_							).input_ids ,							filter_word_delimiter_token=UpperCamelCase_							)

													self.assertEqual(" ".join([p.strip() for p in phonemes.split(" |"							)]							).strip() ,							UpperCamelCase_							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Tuple							=       self.tokenizer_class.from_pretrained(
													    "facebook/wav2vec2-lv-60-espeak-cv-ft" ,							word_delimiter_token=UpperCamelCase_							)
													_snake_case		:	Dict							=       "Hello how are you"

													_snake_case		:	Tuple							=       tokenizer(UpperCamelCase_ ,							phonemizer_lang="en-us"							).input_ids
													_snake_case		:	List[str]							=       tokenizer(UpperCamelCase_ ,							phonemizer_lang="fr-fr"							).input_ids

													self.assertNotEqual(UpperCamelCase_ ,							UpperCamelCase_							)

													_snake_case		:	int							=       tokenizer.decode(UpperCamelCase_							)
													_snake_case		:	Tuple							=       tokenizer.decode(UpperCamelCase_							)

													self.assertEqual(UpperCamelCase_ ,							"h ə l oʊ h aʊ ɑːɹ j uː"							)
													self.assertEqual(UpperCamelCase_ ,							"ɛ l o h aʊ a ʁ j u"							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Union[str, Any]							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)
													_snake_case		:	Any							=       "Hello how Are you"
													_snake_case		:	Optional[Any]							=       "hello how are you"

													_snake_case		:	Union[str, Any]							=       tokenizer(UpperCamelCase_							).input_ids
													_snake_case		:	List[Any]							=       tokenizer(UpperCamelCase_							).input_ids

													self.assertEqual(UpperCamelCase_ ,							UpperCamelCase_							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Optional[Any]							=       self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"							)
													tokenizer.add_tokens(["!", "?"]							)
													tokenizer.add_special_tokens({"cls_token": "$$$"}							)

													# fmt: off
													_snake_case		:	Union[str, Any]							=       [
													    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 392, 392, 393, 392, 392, 393, 394, 394],
													    [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 394, 394],
													]
													# fmt: on

													_snake_case		:	Optional[int]							=       tokenizer.batch_decode(UpperCamelCase_							)
													self.assertEqual(UpperCamelCase_ ,							["k s ɾ ɾ l ɭʲ!?!? $$$", "j ð s j ð s oːɹ $$$"]							)



							@staticmethod
							def 			UpperCamelCase			(		lowercase_ ,							lowercase_							):
													_snake_case		:	int							=       [d[key] for d in offsets]
													return retrieved_list



							def 			UpperCamelCase			(		self							):
													_snake_case		:	str							=       self.get_tokenizer(word_delimiter_token="|"							)
													tokenizer.add_tokens("|"							)

													# fmt: off
													# ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
													_snake_case		:	Any							=       [11, 5, 5, 5, 15, 15, tokenizer.pad_token_id, 15, 15, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 15, 8, 8, 8, tokenizer.word_delimiter_token_id, 98]
													# fmt: on

													_snake_case		:	Any							=       tokenizer.decode(UpperCamelCase_ ,							output_char_offsets=UpperCamelCase_ ,							filter_word_delimiter_token=UpperCamelCase_							)
													# check Wav2Vec2CTCTokenizerOutput keys for char
													self.assertEqual(len(outputs.keys()							) ,							2							)
													self.assertTrue("text" in outputs							)
													self.assertTrue("char_offsets" in outputs							)
													self.assertTrue(isinstance(UpperCamelCase_ ,							UpperCamelCase_							)							)

													# check that order of chars is correct and identical for both outputs
													self.assertEqual(" ".join(self.get_from_offsets(outputs["char_offsets"] ,							"char"							)							) ,							outputs.text							)
													self.assertListEqual(
													    self.get_from_offsets(outputs["char_offsets"] ,							"char"							) ,							["k", "s", "ɾ", "ɾ", "|", "ɾ", "l", "|", "ɭʲ"]							)

													# check that offsets are actually correct for char
													# 0-1 is 11, 1-4 is 5, 4-6 is first 15, 6-7 is <pad> (thus not shown), 7-9 is second 15, 9-10 is word_delimiter_token,
													# 10-11 is <pad> (thus not shown), 11-12 is third 15, 12-15 is 8, 15-16 is word_delimiter_token, 16-17 is 98
													self.assertListEqual(
													    self.get_from_offsets(outputs["char_offsets"] ,							"start_offset"							) ,							[0, 1, 4, 7, 9, 11, 12, 15, 16]							)
													self.assertListEqual(
													    self.get_from_offsets(outputs["char_offsets"] ,							"end_offset"							) ,							[1, 4, 6, 9, 10, 12, 15, 16, 17]							)



							def 			UpperCamelCase			(		self							):
													_snake_case		:	Dict							=       self.get_tokenizer(word_delimiter_token="|"							)

													def check_list_tuples_equal(lowercase_ ,							lowercase_							):
																			self.assertTrue(isinstance(UpperCamelCase_ ,							UpperCamelCase_							)							)
																			self.assertTrue(isinstance(outputs_list[0] ,							UpperCamelCase_							)							)

																			# transform list to ModelOutput
																			_snake_case		:	int							=       WavaVecaPhonemeCTCTokenizerOutput(
																			    {k: [d[k] for d in outputs_list] for k in outputs_list[0]}							)

																			self.assertListEqual(outputs_batch["text"] ,							outputs_batch_a["text"]							)

																			def recursive_check(lowercase_ ,							lowercase_							):
																									if isinstance(UpperCamelCase_ ,							UpperCamelCase_							):
																															[recursive_check(UpperCamelCase_ ,							UpperCamelCase_							) for la, la in zip(UpperCamelCase_ ,							UpperCamelCase_							)]
																									self.assertEqual(UpperCamelCase_ ,							UpperCamelCase_							)

																			if "char_offsets" in outputs_batch:
																									recursive_check(outputs_batch["char_offsets"] ,							outputs_batch_a["char_offsets"]							)

        # fmt: off
													_snake_case		:	str							=       [
													    [11, 5, 15, tokenizer.pad_token_id, 15, 4, 8, 98, 32, 32, 32, 32, 4, 33, tokenizer.word_delimiter_token_id, 32, 32, 33, 34, 34],
													    [24, 22, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 24, 22, 22, 22, 4, 5, 77, tokenizer.pad_token_id, 22, 22, 4, 34, 34, 34, 34],
													]
													# fmt: on

													# We assume that `decode` works as expected. All we will check now is
													# the output type is correct and the output is identical to `decode`

													# char
													_snake_case		:	List[str]							=       tokenizer.batch_decode(UpperCamelCase_ ,							output_char_offsets=UpperCamelCase_							)
													_snake_case		:	Tuple							=       [tokenizer.decode(UpperCamelCase_ ,							output_char_offsets=UpperCamelCase_							) for ids in sample_ids]
													check_list_tuples_equal(UpperCamelCase_ ,							UpperCamelCase_							)



							@unittest.skip("Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes"							)
							def 			UpperCamelCase			(		self							):
													pass



							@unittest.skip("Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"							)
							def 			UpperCamelCase			(		self							):
													pass



							@unittest.skip("encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency"							)
							def 			UpperCamelCase			(		self							):
													pass



							@unittest.skip("Wav2Vec2PhonemeModel has no max model length => no testing"							)
							def 			UpperCamelCase			(		self							):
													pass



							def 			UpperCamelCase			(		self							):
													_snake_case		:	List[Any]							=       self.get_tokenizers(do_lower_case=UpperCamelCase_							)
													for tokenizer in tokenizers:
																			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
																									_snake_case		:	Union[str, Any]							=       tokenizer.vocab_size
																									_snake_case		:	List[Any]							=       len(UpperCamelCase_							)

																									self.assertNotEqual(UpperCamelCase_ ,							0							)

																									# We usually have added tokens from the start in tests because our vocab fixtures are
																									# smaller than the original vocabs - let's not assert this
																									# self.assertEqual(vocab_size, all_size)

																									_snake_case		:	Tuple							=       ["aaaaa bbbbbb", "cccccccccdddddddd"]
																									_snake_case		:	Union[str, Any]							=       tokenizer.add_tokens(UpperCamelCase_							)
																									_snake_case		:	Optional[int]							=       tokenizer.vocab_size
																									_snake_case		:	Dict							=       len(UpperCamelCase_							)

																									self.assertNotEqual(UpperCamelCase_ ,							0							)
																									self.assertEqual(UpperCamelCase_ ,							UpperCamelCase_							)
																									self.assertEqual(UpperCamelCase_ ,							len(UpperCamelCase_							)							)
																									self.assertEqual(UpperCamelCase_ ,							all_size + len(UpperCamelCase_							)							)

																									_snake_case		:	Optional[int]							=       tokenizer.encode("aaaaa bbbbbb low cccccccccdddddddd l" ,							add_special_tokens=UpperCamelCase_							)

																									self.assertGreaterEqual(len(UpperCamelCase_							) ,							4							)
																									self.assertGreater(tokens[0] ,							tokenizer.vocab_size - 1							)
																									self.assertGreater(tokens[-3] ,							tokenizer.vocab_size - 1							)

																									_snake_case		:	int							=       {"eos_token": ">>>>|||<||<<|<<", "pad_token": "<<<<<|||>|>>>>|>"}
																									_snake_case		:	str							=       tokenizer.add_special_tokens(UpperCamelCase_							)
																									_snake_case		:	Dict							=       tokenizer.vocab_size
																									_snake_case		:	Optional[int]							=       len(UpperCamelCase_							)

																									self.assertNotEqual(UpperCamelCase_ ,							0							)
																									self.assertEqual(UpperCamelCase_ ,							UpperCamelCase_							)
																									self.assertEqual(UpperCamelCase_ ,							len(UpperCamelCase_							)							)
																									self.assertEqual(UpperCamelCase_ ,							all_size_a + len(UpperCamelCase_							)							)

																									_snake_case		:	str							=       tokenizer.encode(
																									    ">>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l" ,							add_special_tokens=UpperCamelCase_							)

																									self.assertGreaterEqual(len(UpperCamelCase_							) ,							6							)
																									self.assertGreater(tokens[0] ,							tokenizer.vocab_size - 1							)
																									self.assertGreater(tokens[0] ,							tokens[1]							)
																									self.assertGreater(tokens[-3] ,							tokenizer.vocab_size - 1							)
																									self.assertGreater(tokens[-3] ,							tokens[-4]							)
																									self.assertEqual(tokens[0] ,							tokenizer.eos_token_id							)
																									self.assertEqual(tokens[-3] ,							tokenizer.pad_token_id							)



							@unittest.skip("The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode."							)
							def 			UpperCamelCase			(		self							):
													pass



							@unittest.skip("The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode."							)
							def 			UpperCamelCase			(		self							):
													pass



							def 			UpperCamelCase			(		self							):
													_snake_case		:	str							=       self.get_tokenizers(fast=UpperCamelCase_ ,							do_lower_case=UpperCamelCase_							)
													for tokenizer in tokenizers:
																			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
																									_snake_case		:	Tuple							=       ["ð", "ɪ", "s", "ɪ", "z", "ɐ", "t", "ɛ", "k", "s", "t"]
																									_snake_case		:	Optional[int]							=       tokenizer.convert_tokens_to_string(UpperCamelCase_							)

																									self.assertIsInstance(output["text"] ,							UpperCamelCase_							)







"""simple docstring"""
import argparse
import json
import os

from tensorflow.core.protobuf.saved_model_pba import SavedModel


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case : Optional[Any]     		=		"""."""

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
snake_case : List[str]     		=		[
    """Assert""",
    """AssignVariableOp""",
    """EmptyTensorList""",
    """MergeV2Checkpoints""",
    """ReadVariableOp""",
    """ResourceGather""",
    """RestoreV2""",
    """SaveV2""",
    """ShardedFilename""",
    """StatefulPartitionedCall""",
    """StaticRegexFullMatch""",
    """VarHandleOp""",
]


def 							A						(				__snake_case: Optional[Any] ,     __snake_case: Tuple ,     __snake_case: Any  )    ->		int:

       """simple docstring"""





       __magic_name__      				=    SavedModel()
       __magic_name__      				=    []

       with open(os.path.join(__snake_case ,     'utils' ,     'tf_ops' ,     'onnx.json'  )  ) as f:
              __magic_name__      				=    json.load(__snake_case  )['opsets']

       for i in range(1 ,     opset + 1  ):
              onnx_ops.extend(onnx_opsets[str(__snake_case  )]  )

       with open(__snake_case ,     'rb'  ) as f:
              saved_model.ParseFromString(f.read()  )

       __magic_name__      				=    set()

       # Iterate over every metagraph in case there is more than one (a saved model can contain multiple graphs)
       for meta_graph in saved_model.meta_graphs:
              # Add operations in the graph definition
              model_op_names.update(node.op for node in meta_graph.graph_def.node  )

              # Go through the functions in the graph definition
              for func in meta_graph.graph_def.library.function:
                     # Add operations in each function
                     model_op_names.update(node.op for node in func.node_def  )

    # Convert to list, sorted if you want
       __magic_name__      				=    sorted(__snake_case  )
       __magic_name__      				=    []

       for op in model_op_names:
              if op not in onnx_ops and op not in INTERNAL_OPS:
                     incompatible_ops.append(__snake_case  )

       if strict and len(__snake_case  ) > 0:
              raise Exception(F"""Found the following incompatible ops for the opset {opset}:\n""" + incompatible_ops  )
       elif len(__snake_case  ) > 0:
              print(F"""Found the following incompatible ops for the opset {opset}:"""  )
              print(*__snake_case ,     sep='\n'  )
       else:
              print(F"""The saved model {saved_model_path} can properly be converted with ONNX."""  )


if __name__ == "__main__":
 snake_case : Optional[Any]     		=		argparse.ArgumentParser()
 parser.add_argument("""--saved_model_path""", help="""Path of the saved model to check (the .pb file).""")
 parser.add_argument(
     """--opset""", default=1_2, type=int, help="""The ONNX opset against which the model has to be tested."""
 )
 parser.add_argument(
     """--framework""", choices=["""onnx"""], default="""onnx""", help="""Frameworks against which to test the saved model."""
 )
 parser.add_argument(
     """--strict""", action="""store_true""", help="""Whether make the checking strict (raise errors) or not (raise warnings)"""
 )
 snake_case : Any     		=		parser.parse_args()

 if args.framework == "onnx":
  onnx_compliancy(args.saved_model_path, args.strict, args.opset)